Users who design content (e.g. content designers) often utilize a variety of fonts as part of content creation, such as to generate marketing materials, presentations, books, and so forth. These fonts are utilized to produce text that conveys information to an audience in the content created. As such, the fonts utilized in content creation are one of the major elements in content design. The number of fonts available to these users is continually increasing with tens of thousands of fonts currently available. As such, identifying the exact font that a user who designs content feels best conveys the desired information and best fits other design elements (e.g., images) of the content can be a difficult task. In some instances, a user who designs content is able to identify a font that is similar in appearance to what is desired by the user. In other instances, the user could have settled on a font to utilize for the content creation, but may want to find a font, similar in appearance, that may provide an even better fit for the desired content. As such, these users may wish to identify fonts that are similar to a currently selected font. As a users decides between different fonts, it is helpful to be able to preview how the content design looks with various fonts.
Identifying fonts that are similar to a given font is a known problem. Under the current state of the art, a user can utilize a list of pre-determined font representations, such as a feature vector of a font, to identify fonts that are similar to a given font. For fonts installed on the user's computing device, the user can preview characters of the similar fonts. This preview gives users an idea of what the font will look like when applied to their content design before applying the font to the design. However, under the current state of the art, a user is limited to previewing only those fonts that have been installed on the user's computer system.